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Introductory econometrics for finance / Chris Brooks.

Por: Tipo de material: TextoTextoIdioma: Inglés Detalles de publicación: Cambridge : Cambridge University Press, 2014.Edición: Tercera ediciónDescripción: xxiv, 716 páginas : ilustraciones, gráficas a color ; 25 cmISBN:
  • 9781107661455
Tema(s): Clasificación LoC:
  • HG 173  .B76 2014
Contenidos incompletos:
List of tables, xv -- List of boxes, xvii -- List of screenshots, xix -- Preface to the third editions, xxi -- Acknowledgements, xxv -- 1. Introduction, 1 -- Mathematical and statistical foundations, 28 -- A brief overview of the classical linear regression model, 75 -- 4Futher development and analysis of the classical linear regression model, 134 -- 5. classical linear regression model asumptions and diagnostic tests, 179 -- 6. Univariate time series modelling and forecasting, 251 -- 7. Multivariate models, 305 -- 8.Modelling long-run relationships in finance, 353 -- 9.Modelling volatility and correlation, 415 -- 10. Switching models, 490 -- 11. Panel data, 526 -- 12. Limited dependent variable models -- 13. Simulation methods, 591 -- 14. Conducting empirical research or doing a proyect or dissertation in finanance, 626 -- Appendix 1. Sources of data used in this book, 667 -- Appendix 2. Tables of statistical distributions, 668 -- Glossary, 680 -- References, 697 -- Index, 710.
Resumen: This bestselling and thoroughly classroom-tested textbook is a complete resource for finance students. A comprehensive and illustrated discussion of the most common empirical approaches in finance prepares students for using econometrics in practice, while detailed case studies help them understand how the techniques are used in relevant financial contexts. Worked examples from the latest version of the popular statistical software EViews guide students to implement their own models and interpret results. Learning outcomes, key concepts and end-of-chapter review questions (with full solutions online) highlight the main chapter takeaways and allow students to self-assess their understanding. Building on the successful data- and problem-driven approach of previous editions, this third edition has been updated with new data, extensive examples and additional introductory material on mathematics, making the book more accessible to students encountering econometrics for the first time. A companion website, with numerous student and instructor resources, completes the learning packag.
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Monografía - Colección General SUCURSAL JUAN PABLO DUARTE Estantería HG 173 .B76 2014 (Navegar estantería(Abre debajo)) Disponible 1049683

List of figures, xii -- List of tables, xv -- List of boxes, xvii -- List of screenshots, xix -- Preface to the third editions, xxi -- Acknowledgements, xxv -- 1. Introduction, 1 -- Mathematical and statistical foundations, 28 -- A brief overview of the classical linear regression model, 75 -- 4Futher development and analysis of the classical linear regression model, 134 -- 5. classical linear regression model asumptions and diagnostic tests, 179 -- 6. Univariate time series modelling and forecasting, 251 -- 7. Multivariate models, 305 -- 8.Modelling long-run relationships in finance, 353 -- 9.Modelling volatility and correlation, 415 -- 10. Switching models, 490 -- 11. Panel data, 526 -- 12. Limited dependent variable models -- 13. Simulation methods, 591 -- 14. Conducting empirical research or doing a proyect or dissertation in finanance, 626 -- Appendix 1. Sources of data used in this book, 667 -- Appendix 2. Tables of statistical distributions, 668 -- Glossary, 680 -- References, 697 -- Index, 710.

This bestselling and thoroughly classroom-tested textbook is a complete resource for finance students. A comprehensive and illustrated discussion of the most common empirical approaches in finance prepares students for using econometrics in practice, while detailed case studies help them understand how the techniques are used in relevant financial contexts. Worked examples from the latest version of the popular statistical software EViews guide students to implement their own models and interpret results. Learning outcomes, key concepts and end-of-chapter review questions (with full solutions online) highlight the main chapter takeaways and allow students to self-assess their understanding. Building on the successful data- and problem-driven approach of previous editions, this third edition has been updated with new data, extensive examples and additional introductory material on mathematics, making the book more accessible to students encountering econometrics for the first time. A companion website, with numerous student and instructor resources, completes the learning packag.

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